Head coach data science @neuefische, @pyladieshamburg organizer , vice chair on the @python Software Verband, managing member @PSF and part of the D&I PSF work group
geom = d3.json(
"https://raw.githubusercontent.com/neocarto/bertin/main/data/world.geojson"
)
m = gender ? 0.1 : 2 / 3
bertindata = bertin.merge(geom, "NAMEen", data, "country")
individualsusinginternetbygender = FileAttachment("IndividualsUsingInternetByGender.xlsx").xlsx()
sheet_name = individualsusinginternetbygender.sheetNames[0]
headers = individualsusinginternetbygender.sheet(sheet_name)[2]
max_w_imbalance = d3.max(data, (d) => d.imbalance_f)
max_m_imbalance = d3.max(data, (d) => d.imbalance_m)
avg_w = d3.mean(data, (d) => d.female)
avg_m = d3.mean(data, (d) => d.male)
avg_m - avg_w
bertin = require(`bertin@${lastpatch}`)
d3 = require("d3@7", "d3-geo-projection@4")
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